Senior Data Engineer – Cloud‑Native AWS & Python

About the role

We are seeking a Senior Data Engineer to design, build, and optimise cloud‑native data platforms on Amazon Web Services using Python. The role will create scalable ETL/ELT pipelines, data warehouses and analytics solutions for a variety of clients.

Key responsibilities

• Architect, implement and maintain high‑performance data pipelines (ETL/ELT) using Python and native AWS services.
• Design robust data models (star schema, snowflake, data vault) for analytical and reporting needs.
• Optimise query performance and tune large datasets in cloud data warehouses.
• Implement infrastructure as code with Terraform or CloudFormation and integrate pipelines into CI/CD workflows.
• Establish data quality monitoring, logging, alerting and governance standards.

Required profile

• 5+ years of professional data engineering experience.
• Expert proficiency in Python for data manipulation and pipeline development.
• Deep hands‑on experience with core AWS services for data (S3, Glue, Lambda, EMR, Kinesis, Redshift, Aurora).
• Proven experience with modern data warehouses such as Snowflake, Amazon Redshift, Google BigQuery or Azure Synapse.
• Strong SQL skills and ability to write and optimise complex queries.
• Understanding of containerisation and orchestration (Docker, Kubernetes).
• Fluent English communication and availability within the CET time‑zone (±3 hours).

Required skills

• Python (Pandas, PySpark)
• AWS S3, Glue, Lambda, EMR, Kinesis, Redshift, Aurora
• Snowflake, Google BigQuery, Azure Synapse
• SQL
• Docker, Kubernetes
• Terraform, CloudFormation
• Apache Airflow
• Kafka, Flink